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Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019

Background: Malaria continues to be a major public health problem in Malawi and the greatest load of mortality and morbidity occurs in children five years and under. However, there is no information yet regarding trends and predictions of malaria incidence in children five years and under at distric...

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Autores principales: Gondwe, Theodore, Yang, Yongi, Yosefe, Simeon, Kasanga, Maisa, Mulula, Griffin, Luwemba, Mphatso Prince, Jere, Annie, Daka, Victor, Mudenda, Tobela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657219/
https://www.ncbi.nlm.nih.gov/pubmed/34886507
http://dx.doi.org/10.3390/ijerph182312784
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author Gondwe, Theodore
Yang, Yongi
Yosefe, Simeon
Kasanga, Maisa
Mulula, Griffin
Luwemba, Mphatso Prince
Jere, Annie
Daka, Victor
Mudenda, Tobela
author_facet Gondwe, Theodore
Yang, Yongi
Yosefe, Simeon
Kasanga, Maisa
Mulula, Griffin
Luwemba, Mphatso Prince
Jere, Annie
Daka, Victor
Mudenda, Tobela
author_sort Gondwe, Theodore
collection PubMed
description Background: Malaria continues to be a major public health problem in Malawi and the greatest load of mortality and morbidity occurs in children five years and under. However, there is no information yet regarding trends and predictions of malaria incidence in children five years and under at district hospital level, particularly at Nsanje district hospital. Aim: Therefore, this study aimed at investigating the trends of malaria morbidity and mortality in order to design appropriate interventions on the best approach to contain the disease in the near future. Methodology: Trend analysis of malaria morbidity and mortality together with time series analysis using the SARIMA (Seasonal Autoregressive Integrated Moving Average) model was used to predict malaria incidence in Nsanje district. Results: The SARIMA model used malaria cases from 2015 to 2019 and created the best model to forecast the malaria cases in Nsanje from 2020 to 2022. An SARIMA (0, 1, 2) (0,1,1)(12) was suitable for forecasting the incidence of malaria for Nsanje. Conclusion: The mortality and morbidity trend showed that malaria cases were growing at a fluctuating rate at Nsanje district hospital. The relative errors between the actual values and predicted values indicated that the predicted values matched the actual values well. Therefore, the model proved that it was adequate to forecast monthly malaria cases and it had a good fit, hence, was appropriate for this study
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spelling pubmed-86572192021-12-10 Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019 Gondwe, Theodore Yang, Yongi Yosefe, Simeon Kasanga, Maisa Mulula, Griffin Luwemba, Mphatso Prince Jere, Annie Daka, Victor Mudenda, Tobela Int J Environ Res Public Health Article Background: Malaria continues to be a major public health problem in Malawi and the greatest load of mortality and morbidity occurs in children five years and under. However, there is no information yet regarding trends and predictions of malaria incidence in children five years and under at district hospital level, particularly at Nsanje district hospital. Aim: Therefore, this study aimed at investigating the trends of malaria morbidity and mortality in order to design appropriate interventions on the best approach to contain the disease in the near future. Methodology: Trend analysis of malaria morbidity and mortality together with time series analysis using the SARIMA (Seasonal Autoregressive Integrated Moving Average) model was used to predict malaria incidence in Nsanje district. Results: The SARIMA model used malaria cases from 2015 to 2019 and created the best model to forecast the malaria cases in Nsanje from 2020 to 2022. An SARIMA (0, 1, 2) (0,1,1)(12) was suitable for forecasting the incidence of malaria for Nsanje. Conclusion: The mortality and morbidity trend showed that malaria cases were growing at a fluctuating rate at Nsanje district hospital. The relative errors between the actual values and predicted values indicated that the predicted values matched the actual values well. Therefore, the model proved that it was adequate to forecast monthly malaria cases and it had a good fit, hence, was appropriate for this study MDPI 2021-12-03 /pmc/articles/PMC8657219/ /pubmed/34886507 http://dx.doi.org/10.3390/ijerph182312784 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gondwe, Theodore
Yang, Yongi
Yosefe, Simeon
Kasanga, Maisa
Mulula, Griffin
Luwemba, Mphatso Prince
Jere, Annie
Daka, Victor
Mudenda, Tobela
Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019
title Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019
title_full Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019
title_fullStr Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019
title_full_unstemmed Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019
title_short Epidemiological Trends of Malaria in Five Years and under Children of Nsanje District in Malawi, 2015–2019
title_sort epidemiological trends of malaria in five years and under children of nsanje district in malawi, 2015–2019
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8657219/
https://www.ncbi.nlm.nih.gov/pubmed/34886507
http://dx.doi.org/10.3390/ijerph182312784
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